Post #786

Graph Machine Learning @ ICML 2023 Just finished a new Medium post summarizing Graph ML papers seen at ICML 2023 with some additional photos from Hawaii to make the text less boring 😉 What you can find inside: - Graph Transformers: Sparser, Faster, and Directed - Theory: VC dimension of GNNs, deep dive in over-squashing - New GNN architectures: delays and half-hops - Generative Models - Stable Diffusion for Molecules, Discrete diffusion - Geometric Learning: Geometric WL, Clifford Algebras - Molecules: 2D-3D pretraining, Uncertainty Estimation in MD - Materials & Proteins: CLIP for proteins, Ewald Message Passing, Equivariant Augmentations - Cool Applications: Algorithmic reasoning, Inductive KG completion, GNNs for mass spectra